Definition
Marginal ROAS is the incremental revenue generated by the next unit of ad spend. It is the metric you want for scaling decisions under diminishing returns.
Formula
Marginal ROAS = incremental revenue / incremental ad spend
Example
If an extra $10k of spend generates $25k of incremental revenue, marginal ROAS = $25k / $10k = 2.5.
How to use it
- Use marginal ROAS (or incremental profit) to decide when to scale or cut spend.
- Average ROAS can remain high even when marginal ROAS falls below break-even.
- Marginal ROAS is best estimated from experiments or response curves, not attribution alone.
Common mistakes
- Scaling based on average ROAS rather than marginal profit.
- Ignoring margin/variable costs (revenue-only ROAS can mislead).
Why this matters
This term matters because it affects how you interpret performance and make budget decisions. If you use inconsistent definitions or windows, ROAS/CPA can look "better" while profit gets worse.
Practical checklist
- Write a 1-line definition for "Marginal ROAS" that your team will use consistently.
- Keep the time window consistent (weekly/monthly/quarterly) when comparing trends.
- Segment results (channel/plan/cohort) before drawing big conclusions from blended averages.
- Use a calculator that references this term (e.g., Marginal ROAS Calculator) to sanity-check assumptions.
- Read the related guide (e.g., Marginal ROAS: how to scale ads with diminishing returns) for context and common pitfalls.
Where to use this on MetricKit
Calculators
- Marginal ROAS Calculator: Estimate diminishing returns and find the profit-maximizing ad spend from a simple response curve.
Guides
- Marginal ROAS: how to scale ads with diminishing returns: A practical guide to marginal ROAS: why average ROAS misleads at scale, how diminishing returns work, and how to pick a profit-maximizing spend level.
- Attribution vs incrementality: what to trust, when, and how to test: A practical guide to attribution vs incrementality: common attribution models, window pitfalls, how MER/marginal ROAS fit in, and how to run holdout/geo tests.